Network Travel Time Estimation for Freight Planning Using Entry-Exit Data

Quarterly Reports Other Documents Final Report
March 2014 Final Report

Primary Investigator

Teresa Adams
Professor and Director of CFIRE
University of Wisconsin-Madison
271 Computer Aided Engineering
1410 Engineering Drive
Madison, WI 53706-1608
Tel: 608/263-3175
Fax: 608/263-2512
E-mail: adams@engr.wisc.edu

Abstract

The network travel time information is necessary for industries, carriers or freight planners to develop fleet truck routing strategies. Furthermore, the dynamic estimation of network travel time, especially on major freight corridors or areas of busy freight operations, can be used to determine the best timing of freight delivery in order to avoid congestion and to determine the variability of travel time and transportation costs associated with industrial site selection. Considering a given network or corridor, traffic enter and exit over a period of time, each having a time stamp for the entry and exit. This research is to use the time stamps and network entry/exit location information to estimate the network link travel times for the purpose of truck fleet operations and corridor performance. There are two possible goals: (1) develop a mechanism and analytical methodologies to estimate the network travel time for trucks, particularly in a congested area; (2) develop appropriate methods for optimal operations of truck fleets using the travel time estimates on the network. The objective of this proposal is to focus on the first.

The wide use of Bluetooth technology and GPS data has created a situation in which vehicles (including trucks) entry and exit information on a network is known. The challenge is how to use this limited, concise information to infer the network performance and improve commercial vehicles operations and planning. A broader impact of this study is that the methodology to be developed will show that entry/exit time stamps are sufficient to archive for network performance modeling purposes – which will greatly reduce the amount of data to track and archive. The method may be used to assess performance of networks of other modes such as subway networks, where passengers’ entry and exit information is tracked at check in/out points, and networked toll road systems as in some other countries,  where entry/exit data is recorded at toll booths. There are two cases.

 

  1. Truck corridor network performance estimation with known individual truck routes and known network entry/exit time and location. This case happens on a national corridor network.
  2. Local network performance estimation with unknown individual truck routes and only known network entry/exit time and location. In this case, the routes of truckers need to be estimated first in accordance with their route choice behavior. This case likely represents a dense transportation network such the Greater Chicago area.

 

Objectives

An analytical method to map entry/exit information into the entire network performance will be built on the widely available Bluetooth data and other GPS data. The method will also apply to metro system performance estimation using their available data. Some preliminary studies have been conducted for about a year. Partial results indicate a promising outcome.

Tasks

  1. Review of literature on travel time estimation techniques, truck fleet routing and delivery operations.
  2. Develop analytical models for link travel time estimation using known routes and known entry/exit information. This is according to Case A above. This task sets the basic analytical models for the subsequent studies.
  3. Explore analytical models for link travel time estimation only using known entry/exit information. This is according to Case B above. This task considers truckers’ route choice behavior and will highlight research challenges and issues.
  4. Improve operations/planning for freight carriers. Utilizing the estimated link travel times with the methodologies developed above, freight carriers make better freight planning/operations through improved routing/scheduling.
  5. Conduct numerical tests.
  6. Final report/publication.

Project Information

  • Duration: 12 months
  • Dates: November 1, 2012 – October 31, 2013
  • Budget: $160,000 ($50,000 in matching funds)
  • Student Involvement: One graduate student
  • Modal Orientation: Highway
  • Project ID: CFIRE 07-07
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